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Machine Learning with Python

Machine Learning with Python

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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho

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Machine Learning with PythonRed:Machine Learning with PythonIndia4 969Educación2 421

📈 Análisis del canal de Telegram Machine Learning with Python

El canal Machine Learning with Python (@codeprogrammer) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 67 795 suscriptores, ocupando la posición 2 421 en la categoría Educación y el puesto 4 969 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 67 795 suscriptores.

Según los últimos datos del 19 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 115, y en las últimas 24 horas de -27, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 4.60%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.51% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 3 120 visualizaciones. En el primer día suele acumular 1 026 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 5.
  • Intereses temáticos: El contenido se centra en temas clave como insidead, learning, degree, evaluation, algorithm.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 20 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Educación.

67 795
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-2724 horas
-147 días
+11530 días
Archivo de publicaciones
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